Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
22 Related JoVE Articles!
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (https://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Adhesion Frequency Assay for In Situ Kinetics Analysis of Cross-Junctional Molecular Interactions at the Cell-Cell Interface
Institutions: Georgia Institute of Technology .
The micropipette adhesion assay was developed in 1998 to measure two-dimensional (2D) receptor-ligand binding kinetics1
. The assay uses a human red blood cell (RBC) as adhesion sensor and presenting cell for one of the interacting molecules. It employs micromanipulation to bring the RBC into contact with another cell that expresses the other interacting molecule with precisely controlled area and time to enable bond formation. The adhesion event is detected as RBC elongation upon pulling the two cells apart. By controlling the density of the ligands immobilized on the RBC surface, the probability of adhesion is kept in mid-range between 0 and 1. The adhesion probability is estimated from the frequency of adhesion events in a sequence of repeated contact cycles between the two cells for a given contact time. Varying the contact time generates a binding curve. Fitting a probabilistic model for receptor-ligand reaction kinetics1
to the binding curve returns the 2D affinity and off-rate.
The assay has been validated using interactions of Fcγ receptors with IgG Fc1-6
, selectins with glycoconjugate ligands6-9
, integrins with ligands10-13
, homotypical cadherin binding14
, T cell receptor and coreceptor with peptide-major histocompatibility complexes15-19
The method has been used to quantify regulations of 2D kinetics by biophysical factors, such as the membrane microtopology5
, membrane anchor2
, molecular orientation and length6
, carrier stiffness9
, and impingement force20
, as well as biochemical factors, such as modulators of the cytoskeleton and membrane microenvironment where the interacting molecules reside and the surface organization of these molecules15,17,19
The method has also been used to study the concurrent binding of dual receptor-ligand species3,4
, and trimolecular interactions19
using a modified model21
The major advantage of the method is that it allows study of receptors in their native membrane environment. The results could be very different from those obtained using purified receptors17
. It also allows study of the receptor-ligand interactions in a sub-second timescale with temporal resolution well beyond the typical biochemical methods.
To illustrate the micropipette adhesion frequency method, we show kinetics measurement of intercellular adhesion molecule 1 (ICAM-1) functionalized on RBCs binding to integrin αL
on neutrophils with dimeric E-selectin in the solution to activate αL
Bioengineering, Issue 57, Two-dimensional binding, affinity and kinetics, micropipette manipulation, receptor-ligand interaction
Microfluidic On-chip Capture-cycloaddition Reaction to Reversibly Immobilize Small Molecules or Multi-component Structures for Biosensor Applications
Institutions: Massachusetts General Hospital.
Methods for rapid surface immobilization of bioactive small molecules with control over orientation and immobilization density are highly desirable for biosensor and microarray applications. In this Study, we use a highly efficient covalent bioorthogonal [4+2] cycloaddition reaction between trans
-cyclooctene (TCO) and 1,2,4,5-tetrazine (Tz) to enable the microfluidic immobilization of TCO/Tz-derivatized molecules. We monitor the process in real-time under continuous flow conditions using surface plasmon resonance (SPR). To enable reversible immobilization and extend the experimental range of the sensor surface, we combine a non-covalent antigen-antibody capture component with the cycloaddition reaction. By alternately presenting TCO or Tz moieties to the sensor surface, multiple capture-cycloaddition processes are now possible on one sensor surface for on-chip assembly and interaction studies of a variety of multi-component structures. We illustrate this method with two different immobilization experiments on a biosensor chip; a small molecule, AP1497 that binds FK506-binding protein 12 (FKBP12); and the same small molecule as part of an immobilized and in situ-
Chemistry, Issue 79, Organic Chemicals, Macromolecular Substances, Chemistry and Materials (General), Surface Plasmon Resonance, Bioorthogonal Chemistry, Diels-Alder Cycloaddition Reaction, Small Molecule Immobilization, Binding Kinetics, Immobilized Nanoparticles
Studying Cell Rolling Trajectories on Asymmetric Receptor Patterns
Institutions: MIT - Massachusetts Institute of Technology, MIT - Massachusetts Institute of Technology, Brigham and Women's Hospital and Harvard Medical School.
Lateral displacement of cells orthogonal to a flow stream by rolling on asymmetric receptor patterns presents an opportunity for development of new devices for label-free separation and analysis of cells1
. Such devices may use lateral displacement for continuous-flow separation, or receptor patterns that modulate adhesion to distinguish between different cell phenotypes or levels of receptor expression. Understanding the nature of cell rolling trajectories on receptor-patterned substrates is necessary for engineering of the substrates and design of such devices.
Here, we demonstrate a protocol for studying cell rolling trajectories on asymmetric receptor patterns that support cell rolling adhesion2
. Well-defined, μm-scale patterns of P-selectin receptors were fabricated using microcontact printing on gold-coated slides that were incorporated in a flow chamber. HL60 cells expressing the PSGL-1 ligand 3
were flowed across a field of patterned lines and visualized on an inverted bright field microscope. The cells rolled and tracked along the inclined edges of the patterns, resulting in lateral deflection1
. Each cell typically rolled for a certain distance along the pattern edges (defined as the edge tracking length), detached from the edge, and reattached to a downstream pattern. Although this detachment makes it difficult to track the entire trajectory of a cell from entrance to exit in the flow chamber, particle-tracking software was used to analyze and yield the rolling trajectories of the cells during the time when they were moving on a single receptor-patterned line. The trajectories were then examined to obtain distributions of cell rolling velocities and the edge tracking lengths for each cell for different patterns.
This protocol is useful for quantifying cell rolling trajectories on receptor patterns and relating these to engineering parameters such as pattern angle and shear stress. Such data will be useful for design of microfluidic devices for label-free cell separation and analysis.
Bioengineering, Issue 48, cell rolling, microcontact printing, cell adhesion, cell analysis, cell separation, P-selectin
Computer-assisted Large-scale Visualization and Quantification of Pancreatic Islet Mass, Size Distribution and Architecture
Institutions: University of Chicago, National Institutes of Health, University of Chicago, University of Massachusetts.
The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), and delta-cells (somatostatin) that are embedded in the exocrine tissues and comprise 1-2% of the entire pancreas. There is a close correlation between body and pancreas weight. Total beta-cell mass also increases proportionately to compensate for the demand for insulin in the body. What escapes this proportionate expansion is the size distribution of islets. Large animals such as humans share similar islet size distributions with mice, suggesting that this micro-organ has a certain size limit to be functional. The inability of large animal pancreata to generate proportionately larger islets is compensated for by an increase in the number of islets and by an increase in the proportion of larger islets in their overall islet size distribution. Furthermore, islets exhibit a striking plasticity in cellular composition and architecture among different species and also within the same species under various pathophysiological conditions. In the present study, we describe novel approaches for the analysis of biological image data in order to facilitate the automation of analytic processes, which allow for the analysis of large and heterogeneous data collections in the study of such dynamic biological processes and complex structures. Such studies have been hampered due to technical difficulties of unbiased sampling and generating large-scale data sets to precisely capture the complexity of biological processes of islet biology. Here we show methods to collect unbiased "representative" data within the limited availability of samples (or to minimize the sample collection) and the standard experimental settings, and to precisely analyze the complex three-dimensional structure of the islet. Computer-assisted automation allows for the collection and analysis of large-scale data sets and also assures unbiased interpretation of the data. Furthermore, the precise quantification of islet size distribution and spatial coordinates (i.e. X, Y, Z-positions) not only leads to an accurate visualization of pancreatic islet structure and composition, but also allows us to identify patterns during development and adaptation to altering conditions through mathematical modeling. The methods developed in this study are applicable to studies of many other systems and organisms as well.
Cellular Biology, Issue 49, beta-cells, islets, large-scale analysis, pancreas
Inhibitory Synapse Formation in a Co-culture Model Incorporating GABAergic Medium Spiny Neurons and HEK293 Cells Stably Expressing GABAA Receptors
Institutions: University College London.
Inhibitory neurons act in the central nervous system to regulate the dynamics and spatio-temporal co-ordination of neuronal networks. GABA (γ-aminobutyric acid) is the predominant inhibitory neurotransmitter in the brain. It is released from the presynaptic terminals of inhibitory neurons within highly specialized intercellular junctions known as synapses, where it binds to GABAA
Rs) present at the plasma membrane of the synapse-receiving, postsynaptic neurons. Activation of these GABA-gated ion channels leads to influx of chloride resulting in postsynaptic potential changes that decrease the probability that these neurons will generate action potentials.
During development, diverse types of inhibitory neurons with distinct morphological, electrophysiological and neurochemical characteristics have the ability to recognize their target neurons and form synapses which incorporate specific GABAA
Rs subtypes. This principle of selective innervation of neuronal targets raises the question as to how the appropriate synaptic partners identify each other.
To elucidate the underlying molecular mechanisms, a novel in vitro
co-culture model system was established, in which medium spiny GABAergic neurons, a highly homogenous population of neurons isolated from the embryonic striatum, were cultured with stably transfected HEK293 cell lines that express different GABAA
R subtypes. Synapses form rapidly, efficiently and selectively in this system, and are easily accessible for quantification. Our results indicate that various GABAA
R subtypes differ in their ability to promote synapse formation, suggesting that this reduced in vitro
model system can be used to reproduce, at least in part, the in vivo
conditions required for the recognition of the appropriate synaptic partners and formation of specific synapses. Here the protocols for culturing the medium spiny neurons and generating HEK293 cells lines expressing GABAA
Rs are first described, followed by detailed instructions on how to combine these two cell types in co-culture and analyze the formation of synaptic contacts.
Neuroscience, Issue 93, Developmental neuroscience, synaptogenesis, synaptic inhibition, co-culture, stable cell lines, GABAergic, medium spiny neurons, HEK 293 cell line
Discovering Protein Interactions and Characterizing Protein Function Using HaloTag Technology
Institutions: Promega Corporation, MS Bioworks LLC.
Research in proteomics has exploded in recent years with advances in mass spectrometry capabilities that have led to the characterization of numerous proteomes, including those from viruses, bacteria, and yeast. In comparison, analysis of the human proteome lags behind, partially due to the sheer number of proteins which must be studied, but also the complexity of networks and interactions these present. To specifically address the challenges of understanding the human proteome, we have developed HaloTag technology for protein isolation, particularly strong for isolation of multiprotein complexes and allowing more efficient capture of weak or transient interactions and/or proteins in low abundance. HaloTag is a genetically encoded protein fusion tag, designed for covalent, specific, and rapid immobilization or labelling of proteins with various ligands. Leveraging these properties, numerous applications for mammalian cells were developed to characterize protein function and here we present methodologies including: protein pull-downs used for discovery of novel interactions or functional assays, and cellular localization. We find significant advantages in the speed, specificity, and covalent capture of fusion proteins to surfaces for proteomic analysis as compared to other traditional non-covalent approaches. We demonstrate these and the broad utility of the technology using two important epigenetic proteins as examples, the human bromodomain protein BRD4, and histone deacetylase HDAC1. These examples demonstrate the power of this technology in enabling the discovery of novel interactions and characterizing cellular localization in eukaryotes, which will together further understanding of human functional proteomics.
Cellular Biology, Issue 89, proteomics, HaloTag, protein interactions, mass spectrometry, bromodomain proteins, BRD4, histone deacetylase (HDAC), HDAC cellular assays, and confocal imaging
In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions
Institutions: Pacific Northwest National Laboratory.
Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ
characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3
(bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ
time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ
Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ
IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.
Chemistry, Issue 88, soft landing, mass selected ions, electrospray, secondary ion mass spectrometry, infrared spectroscopy, organometallic, catalysis
Genetically-encoded Molecular Probes to Study G Protein-coupled Receptors
Institutions: The Rockefeller University.
To facilitate structural and dynamic studies of G protein-coupled receptor (GPCR) signaling complexes, new approaches are required to introduce informative probes or labels into expressed receptors that do not perturb receptor function. We used amber codon suppression technology to genetically-encode the unnatural amino acid, p
-azido-L-phenylalanine (azF) at various targeted positions in GPCRs heterologously expressed in mammalian cells. The versatility of the azido group is illustrated here in different applications to study GPCRs in their native cellular environment or under detergent solubilized conditions. First, we demonstrate a cell-based targeted photocrosslinking technology to identify the residues in the ligand-binding pocket of GPCR where a tritium-labeled small-molecule ligand is crosslinked to a genetically-encoded azido amino acid. We then demonstrate site-specific modification of GPCRs by the bioorthogonal Staudinger-Bertozzi ligation reaction that targets the azido group using phosphine derivatives. We discuss a general strategy for targeted peptide-epitope tagging of expressed membrane proteins in-culture and its detection using a whole-cell-based ELISA approach. Finally, we show that azF-GPCRs can be selectively tagged with fluorescent probes. The methodologies discussed are general, in that they can in principle be applied to any amino acid position in any expressed GPCR to interrogate active signaling complexes.
Genetics, Issue 79, Receptors, G-Protein-Coupled, Protein Engineering, Signal Transduction, Biochemistry, Unnatural amino acid, site-directed mutagenesis, G protein-coupled receptor, targeted photocrosslinking, bioorthogonal labeling, targeted epitope tagging
Avidity-based Extracellular Interaction Screening (AVEXIS) for the Scalable Detection of Low-affinity Extracellular Receptor-Ligand Interactions
Institutions: Wellcome Trust Sanger Institute.
Extracellular protein:protein interactions between secreted or membrane-tethered proteins are critical for both initiating intercellular communication and ensuring cohesion within multicellular organisms. Proteins predicted to form extracellular interactions are encoded by approximately a quarter of human genes1
, but despite their importance and abundance, the majority of these proteins have no documented binding partner. Primarily, this is due to their biochemical intractability: membrane-embedded proteins are difficult to solubilise in their native conformation and contain structurally-important posttranslational modifications. Also, the interaction affinities between receptor proteins are often characterised by extremely low interaction strengths (half-lives < 1 second) precluding their detection with many commonly-used high throughput methods2
Here, we describe an assay, AVEXIS (AVidity-based EXtracellular Interaction Screen) that overcomes these technical challenges enabling the detection of very weak protein interactions (t1/2
≤ 0.1 sec) with a low false positive rate3
. The assay is usually implemented in a high throughput format to enable the systematic screening of many thousands of interactions in a convenient microtitre plate format (Fig. 1). It relies on the production of soluble recombinant protein libraries that contain the ectodomain fragments of cell surface receptors or secreted proteins within which to screen for interactions; therefore, this approach is suitable for type I, type II, GPI-linked cell surface receptors and secreted proteins but not for multipass membrane proteins such as ion channels or transporters.
The recombinant protein libraries are produced using a convenient and high-level mammalian expression system4
, to ensure that important posttranslational modifications such as glycosylation and disulphide bonds are added. Expressed recombinant proteins are secreted into the medium and produced in two forms: a biotinylated bait which can be captured on a streptavidin-coated solid phase suitable for screening, and a pentamerised enzyme-tagged (β-lactamase) prey. The bait and prey proteins are presented to each other in a binary fashion to detect direct interactions between them, similar to a conventional ELISA (Fig. 1). The pentamerisation of the proteins in the prey is achieved through a peptide sequence from the cartilage oligomeric matrix protein (COMP) and increases the local concentration of the ectodomains thereby providing significant avidity gains to enable even very transient interactions to be detected. By normalising the activities of both the bait and prey to predetermined levels prior to screening, we have shown that interactions having monomeric half-lives of 0.1 sec can be detected with low false positive rates3
Molecular Biology, Issue 61, Receptor-ligand pairs, Extracellular protein interactions, AVEXIS, Adhesion receptors, Transient/weak interactions, High throughput screening
The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis
Institutions: GE Healthcare Bio-Sciences AB.
In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), a plant cysteine protease, by real-time label-free analysis using Biacore X100. Several cystatin B variants with point mutations in areas of interaction with papain, are produced. For each cystatin B variant we determine its specific binding concentration using calibration-free concentration analysis (CFCA) and compare the values obtained with total protein concentration as determined by A280
. After that, the kinetics of each cystatin B variant binding to papain is measured using single-cycle kinetics (SCK). We show that one of the four cystatin B variants we examine is only partially active for binding. This partial activity, revealed by CFCA, translates to a significant difference in the association rate constant (ka
) and affinity (KD
), compared to the values calculated using total protein concentration. Using CFCA in combination with kinetic analysis in a structure-function study contributes to obtaining reliable results, and helps to make the right interpretation of the interaction mechanism.
Cellular Biology, Issue 37, Protein interaction, Surface Plasmon Resonance, Biacore X100, CFCA, Cystatin B, Papain
In Vitro Reconstitution of Light-harvesting Complexes of Plants and Green Algae
Institutions: VU University Amsterdam.
In plants and green algae, light is captured by the light-harvesting complexes (LHCs), a family of integral membrane proteins that coordinate chlorophylls and carotenoids. In vivo
, these proteins are folded with pigments to form complexes which are inserted in the thylakoid membrane of the chloroplast. The high similarity in the chemical and physical properties of the members of the family, together with the fact that they can easily lose pigments during isolation, makes their purification in a native state challenging. An alternative approach to obtain homogeneous preparations of LHCs was developed by Plumley and Schmidt in 19871
, who showed that it was possible to reconstitute these complexes in vitro
starting from purified pigments and unfolded apoproteins, resulting in complexes with properties very similar to that of native complexes. This opened the way to the use of bacterial expressed recombinant proteins for in vitro
reconstitution. The reconstitution method is powerful for various reasons: (1) pure preparations of individual complexes can be obtained, (2) pigment composition can be controlled to assess their contribution to structure and function, (3) recombinant proteins can be mutated to study the functional role of the individual residues (e.g.,
pigment binding sites) or protein domain (e.g.,
protein-protein interaction, folding). This method has been optimized in several laboratories and applied to most of the light-harvesting complexes. The protocol described here details the method of reconstituting light-harvesting complexes in vitro
currently used in our laboratory,
and examples describing applications of the method are provided.
Biochemistry, Issue 92, Reconstitution, Photosynthesis, Chlorophyll, Carotenoids, Light Harvesting Protein, Chlamydomonas reinhardtii, Arabidopsis thaliana
Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry
Institutions: University of Exeter.
A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.
Biophysics, Issue 91, differential scanning fluorimetry, dissociation constant, protein-ligand interactions, StepOne, cooperativity, WcbI.
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
In Situ Neutron Powder Diffraction Using Custom-made Lithium-ion Batteries
Institutions: University of Sydney, University of Wollongong, Australian Synchrotron, Australian Nuclear Science and Technology Organisation, University of Wollongong, University of New South Wales.
Li-ion batteries are widely used in portable electronic devices and are considered as promising candidates for higher-energy applications such as electric vehicles.1,2
However, many challenges, such as energy density and battery lifetimes, need to be overcome before this particular battery technology can be widely implemented in such applications.3
This research is challenging, and we outline a method to address these challenges using in situ
NPD to probe the crystal structure of electrodes undergoing electrochemical cycling (charge/discharge) in a battery. NPD data help determine the underlying structural mechanism responsible for a range of electrode properties, and this information can direct the development of better electrodes and batteries.
We briefly review six types of battery designs custom-made for NPD experiments and detail the method to construct the ‘roll-over’ cell that we have successfully used on the high-intensity NPD instrument, WOMBAT, at the Australian Nuclear Science and Technology Organisation (ANSTO). The design considerations and materials used for cell construction are discussed in conjunction with aspects of the actual in situ
NPD experiment and initial directions are presented on how to analyze such complex in situ
Physics, Issue 93, In operando, structure-property relationships, electrochemical cycling, electrochemical cells, crystallography, battery performance
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.
Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via
quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
Analyzing Protein Dynamics Using Hydrogen Exchange Mass Spectrometry
Institutions: University of Heidelberg.
All cellular processes depend on the functionality of proteins. Although the functionality of a given protein is the direct consequence of its unique amino acid sequence, it is only realized by the folding of the polypeptide chain into a single defined three-dimensional arrangement or more commonly into an ensemble of interconverting conformations. Investigating the connection between protein conformation and its function is therefore essential for a complete understanding of how proteins are able to fulfill their great variety of tasks. One possibility to study conformational changes a protein undergoes while progressing through its functional cycle is hydrogen-1
H-exchange in combination with high-resolution mass spectrometry (HX-MS). HX-MS is a versatile and robust method that adds a new dimension to structural information obtained by e.g.
crystallography. It is used to study protein folding and unfolding, binding of small molecule ligands, protein-protein interactions, conformational changes linked to enzyme catalysis, and allostery. In addition, HX-MS is often used when the amount of protein is very limited or crystallization of the protein is not feasible. Here we provide a general protocol for studying protein dynamics with HX-MS and describe as an example how to reveal the interaction interface of two proteins in a complex.
Chemistry, Issue 81, Molecular Chaperones, mass spectrometers, Amino Acids, Peptides, Proteins, Enzymes, Coenzymes, Protein dynamics, conformational changes, allostery, protein folding, secondary structure, mass spectrometry
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1
. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2
. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5
to more rigorous statistical models, e.g.
Hidden Markov Models (HMMs)6-8
. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9
, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11
and epigenetic data12
to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2
, the degree of those aversions vary substantially across individuals, such that the subjective value
of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3
to assess the neural representation of the subjective values of risky and ambiguous options4
. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations.
In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity
Analyzing and Building Nucleic Acid Structures with 3DNA
Institutions: Rutgers - The State University of New Jersey, Columbia University .
The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic acid structures. This article presents detailed protocols for a subset of new and popular features available in 3DNA, applicable to both individual structures and ensembles of related structures. Protocol 1 lists the set of instructions needed to download and install the software. This is followed, in Protocol 2, by the analysis of a nucleic acid structure, including the assignment of base pairs and the determination of rigid-body parameters that describe the structure and, in Protocol 3, by a description of the reconstruction of an atomic model of a structure from its rigid-body parameters. The most recent version of 3DNA, version 2.1, has new features for the analysis and manipulation of ensembles of structures, such as those deduced from nuclear magnetic resonance (NMR) measurements and molecular dynamic (MD) simulations; these features are presented in Protocols 4 and 5. In addition to the 3DNA stand-alone software package, the w3DNA web server, located at https://w3dna.rutgers.edu, provides a user-friendly interface to selected features of the software. Protocol 6 demonstrates a novel feature of the site for building models of long DNA molecules decorated with bound proteins at user-specified locations.
Genetics, Issue 74, Molecular Biology, Biochemistry, Bioengineering, Biophysics, Genomics, Chemical Biology, Quantitative Biology, conformational analysis, DNA, high-resolution structures, model building, molecular dynamics, nucleic acid structure, RNA, visualization, bioinformatics, three-dimensional, 3DNA, software